I have a list as follows,
remove_words = [\'abc\', \'deff\', \'pls\']
The following is the data frame which I am having with column name \'
Totally taking @MaxU's pattern!
We can use pd.DataFrame.replace by setting the regex
parameter to True
and passing a dictionary of dictionaries that specifies the pattern and what to replace with for each column.
pat = '|'.join([r'\b{}\b'.format(w) for w in remove_words])
df.assign(new=df.replace(dict(string={pat: ''}), regex=True))
string new
0 abc stack overflow stack overflow
1 abc123 abc123
2 def comedy comedy
3 definitely definitely
4 pls lkjh lkjh
5 pls1234 pls1234